A Compiler for Parallel Exeuction of Numerical Python Programs on ...

3.5.1 Type annotationsType declarations enable the compiler to generate efficient C code. <strong>Python</strong> is a dynamicallytyped language and has no type declaration syntax. For this purpose, an extension wasintroduced to <strong>Python</strong> to declare the type signature <strong>of</strong> a function.In this extension, the programmer creates a special decorator to annotate each functionto be compiled. This decorator declares the types <strong>of</strong> the function’s parameters and <strong>of</strong> itsreturn value. Decorators are annotations added just be<strong>for</strong>e a function definition and area standard <strong>Python</strong> syntax feature.Optionally, the types <strong>of</strong> local variables may also bedeclared in a similar fashion. If no such declarations are provided, the compiler infers thetypes <strong>of</strong> a local variable based on the type <strong>of</strong> the first value assigned to the variable in thefunction. In this framework, a variable cannot change its type within a function.Figure 3.5 shows an example <strong>of</strong> type-declaration syntax. The decorator unpython.typeis added to the function declaration. Types are passed to the decorator as arguments. Ifthe function takes x number <strong>of</strong> parameters, then x + 1 types are required. The first x typesare <strong>for</strong> the parameters and the last type specified is <strong>for</strong> the return type <strong>of</strong> the function. Inthe example, the first type is <strong>for</strong> the parameter n and the second type is <strong>for</strong> the return type.The types <strong>of</strong> sum and i are automatically inferred by the compiler to be int64 which is thedefault integer type. These types can be <strong>for</strong>ced to be int32 by adding type declarations <strong>for</strong>the local variables.1 @unpython . type ( ’ i n t 6 4 ’ , ’ i n t 6 4 ’ )2 def f ( n ) :3 sum = 04 <strong>for</strong> i in range ( n ) :5 sum += i6 return sumFigure 3.5: Example <strong>of</strong> decorator used as a type declarator.3.5.2 <strong>Parallel</strong> annotationsThe <strong>Python</strong> interpreter does not provide any support <strong>for</strong> parallel programming. One wayto take advantage <strong>of</strong> multiple processor cores is to utilize process-based parallelism wheremultiple instances <strong>of</strong> the <strong>Python</strong> interpreter may be launched. Process-based parallelism isnot suitable <strong>for</strong> all types <strong>of</strong> problems and is not considered in this thesis. The only wayto take advantage <strong>of</strong> multiple processor cores within a single <strong>Python</strong> process is to writea multithreaded function in C using an API such as pthreads or OpenMP. However, thecurrent <strong>Python</strong> interpreter is not multithreaded and calling <strong>Python</strong>-C API functions fromtwo different C threads is unsafe. There<strong>for</strong>e, the programmer must be careful about calling25